scholarly journals Plasma miR-181a as a Candidate Diagnostic Biomarker for Kawasaki Disease Patients with Coronary Artery lesions

2020 ◽  
Author(s):  
Yu Peng ◽  
Xiaohui Liu ◽  
Junkai Duan ◽  
Zhao Duan ◽  
Zheng Zou ◽  
...  

Abstract Background: Kawasaki disease (KD) is an acute and systemic vasculitis, and the critical complication in KD patients is coronary artery lesions (CAL). Plasma miR-181a was found dysregulated in a variety of cardiovascular disease. The aim of this study was to define the relationship between the plasma miR-181a levels and CAL in KD. Methods: Plasma miR-181a levels were analyzed by quantitative reverse transcriptase-polymerase chain reaction in 121 patients with KD. Results:We found that plasma miR-181a levels at the acute phase were significantly elevated in KD patients with CAL than those without CAL. Correlation analysis showed that plasma miR-181a levels were positively correlated with the concentrations of CRP (r=0.363, P < 0.05) and NT-proBNP (r=0.389, P < 0.05). Receiver operating characteristic curve analyses showed that plasma miR-181a was of significant prediction value for CAL in KD, the area under receiver operating characteristic curve value for plasma miR-181a in prediction of CAL was 0.747, and the estimated sensitivity and specificity were 75.0% and 68.8%, respectively. Conclusions: Plasma miR-181a is prone to be a candidate biomarker for predicting CAL in KD. Therefore, further investigations are warranted to fully elucidate its role in KD.

2019 ◽  
Vol 30 (7-8) ◽  
pp. 221-228
Author(s):  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
Nicholas Hobbs ◽  
Jigar Shah ◽  
Matthew Harris ◽  
...  

Aims To investigate whether an intraperitoneal contamination index (ICI) derived from combined preoperative levels of C-reactive protein, lactate, neutrophils, lymphocytes and albumin could predict the extent of intraperitoneal contamination in patients with acute abdominal pathology. Methods Patients aged over 18 who underwent emergency laparotomy for acute abdominal pathology between January 2014 and October 2018 were randomly divided into primary and validation cohorts. The proposed intraperitoneal contamination index was calculated for each patient in each cohort. Receiver operating characteristic curve analysis was performed to determine discrimination of the index and cut-off values of preoperative intraperitoneal contamination index that could predict the extent of intraperitoneal contamination. Results Overall, 468 patients were included in this study; 234 in the primary cohort and 234 in the validation cohort. The analyses identified intraperitoneal contamination index of 24.77 and 24.32 as cut-off values for purulent contamination in the primary cohort (area under the curve (AUC): 0.73, P < 0.0001; sensitivity: 84%, specificity: 60%) and validation cohort (AUC: 0.83, P < 0.0001; sensitivity: 91%, specificity: 69%), respectively. Receiver operating characteristic curve analysis also identified intraperitoneal contamination index of 33.70 and 33.41 as cut-off values for feculent contamination in the primary cohort (AUC: 0.78, P < 0.0001; sensitivity: 87%, specificity: 64%) and validation cohort (AUC: 0.79, P < 0.0001; sensitivity: 86%, specificity: 73%), respectively. Conclusions As a predictive measure which is derived purely from biomarkers, intraperitoneal contamination index may be accurate enough to predict the extent of intraperitoneal contamination in patients with acute abdominal pathology and to facilitate decision-making together with clinical and radiological findings.


2021 ◽  
pp. 096228022199595
Author(s):  
Yalda Zarnegarnia ◽  
Shari Messinger

Receiver operating characteristic curves are widely used in medical research to illustrate biomarker performance in binary classification, particularly with respect to disease or health status. Study designs that include related subjects, such as siblings, usually have common environmental or genetic factors giving rise to correlated biomarker data. The design could be used to improve detection of biomarkers informative of increased risk, allowing initiation of treatment to stop or slow disease progression. Available methods for receiver operating characteristic construction do not take advantage of correlation inherent in this design to improve biomarker performance. This paper will briefly review some developed methods for receiver operating characteristic curve estimation in settings with correlated data from case–control designs and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using conditional receiver operating characteristic curves will be demonstrated. The proposed approach will use information about correlation among biomarker values, producing conditional receiver operating characteristic curves that evaluate the ability of a biomarker to discriminate between affected and unaffected subjects in a familial paired design.


Sign in / Sign up

Export Citation Format

Share Document